Peru celebrates 200 years of independence in 2021. Over this period of independent life, and despite the turbulent socio-political scenarios, from internal armed conflict to economic crisis to political instability over the last 40 years, Peru has experienced major changes on its epidemiological and population health profile. Major advancements in maternal and child health as well as in communicable diseases have been achieved in recent decades, and today Peru faces an increasing burden of non-communicable diseases including mental health conditions. In terms of the configuration of the public health system, Peru has also strived to secure country-wide optimal health care, struggling in particular to improve primary health care and intercultural services. The science and technology infrastructure has also evolved, although the need for substantial investments remains if advancing science is to be a national priority. Climate change will also bring significant challenges to population health given Peru's geographical and microclimates diversity. Looking back over the 200-years of independence, we present a summary of key advances in selected health-related fields, thus serving as the basis for reflections on pending agendas and future challenges, in order to look forward to ensuring the future health and wellbeing of the Peruvian population. El Perú cumple 200 años de independencia en 2021. Durante estos dos siglos de vida independiente, junto con periodos sociales y políticos turbulentos, incluyendo un conflicto armado interno, hiperinflación y la inestabilidad política de los últimos 40 años, el Perú ha experimentado importantes cambios en su perfil epidemiológico con repercusiones directas en la salud de la población. En las últimas décadas, los indicadores de salud materno-infantil y de las enfermedades transmisibles muestran mejoría importante, pero el país se enfrenta de manera simultánea a una carga cada vez mayor de enfermedades no transmisibles y de salud mental. En cuanto a los sistemas de salud pública, se han realizado esfuerzos por aumentar la cobertura y calidad de la atención de salud en todo el país, apostándose en particular por mejorar la atención primaria. La ciencia y tecnología relacionadas con la salud también han mejorado, aunque si se quiere que la ciencia sea una prioridad nacional, son necesarias inversiones sustanciales. El cambio climático traerá importantes desafíos para la salud de la población, dada la diversidad geográfica y de microclimas del país. Para conmemorar los 200 años de vida independiente del Perú, presentamos un resumen de avances clave en diversas áreas y temas relacionados con la salud. Este repaso sirve como base para reflexionar sobre agendas y desafíos pendientes y futuros, con el fin de asegurar la salud y el bienestar de la población peruana en las próximas décadas.

Background: Future demographic changes will increase the number of people living with non-communicable diseases. We projected the number of people with type 2 diabetes mellitus (T2DM) in 2035 and 2050 at the global and country levels. Methods: We pooled T2DM prevalence estimates from the Global Burden of Disease Study and population estimates from the United Nations for 188 countries. We computed the absolute number of people with T2DM in 2020 and predicted the future number in 2035 and 2050 under four scenarios for the T2DM prevalence: 1) It held constant, 2) It increased by 50%, 3) It decreased by 10%, and 4) It followed 1990-2019 country-specific past trends. Results: The global number of people with T2DM was 445 million in 2020, and it is projected to increase in 2050 to 730 million if prevalence remains unchanged, 1,095 million if prevalence increases by 50%, 657 million if prevalence decreases by 10%, and 1,153 million if prevalence follows country-specific 1990-2019 past trends. Under all scenarios, Sub-Saharan Africa and lowincome countries had the highest relative increase in the number of people with T2DM. The share of people with T2DM aged <60 years is expected to drop from 5 out of 10 in 2020 to 4 out of 10 people in 2050 under all scenarios. Conclusions: There will be a massive growth in the number of people living with T2DM, and low-income countries and countries in Sub-Saharan Africa will be the most affected. Health systems must be strengthened to ensure optimal care for the future population with T2DM.

Objectives Non-alcoholic fatty liver disease (NAFLD) is a non-communicable disease with a rising prevalence worldwide and with large burden for patients and health systems. To date, the presence of unique phenotypes in patients with NAFLD has not been studied, and their identification could inform precision medicine and public health with pragmatic implications in personalised management and care for patients with NAFLD. Design Cross-sectional and prospective (up to 31 December 2019) analysis of National Health and Nutrition Examination Survey III (1988–1994). Primary and secondary outcomes measures NAFLD diagnosis was based on liver ultrasound. The following predictors informed an unsupervised machine learning algorithm (k-means): body mass index, waist circumference, systolic blood pressure (SBP), plasma glucose, total cholesterol, triglycerides, liver enzymes alanine aminotransferase, aspartate aminotransferase and gamma glutamyl transferase. We summarised (means) and compared the predictors across clusters. We used Cox proportional hazard models to quantify the all-cause mortality risk associated with each cluster. Results 1652 patients with NAFLD (mean age 47.2 years and 51.5% women) were grouped into 3 clusters: anthro-SBP-glucose (6.36%; highest levels of anthropometrics, SBP and glucose), lipid-liver (10.35%; highest levels of lipid and liver enzymes) and average (83.29%; predictors at average levels). Compared with the average phenotype, the anthro-SBP-glucose phenotype had higher all-cause mortality risk (aHR=2.88; 95% CI: 2.26 to 3.67); the lipid-liver phenotype was not associated with higher all-cause mortality risk (aHR=1.11; 95% CI: 0.86 to 1.42). Conclusions There is heterogeneity in patients with NAFLD, whom can be divided into three phenotypes with different mortality risk. These phenotypes could guide specific interventions and management plans, thus advancing precision medicine and public health for patients with NAFLD.

High consumption of sugar-sweetened beverages (SSB) is associated with a high risk of non-communicable diseases. Evidence of SSB consumption is needed to inform SSB-related policies, especially in countries with a high consumption, such as Peru. Using data from Peru’s National Health Survey conducted in 2017–2018, the consumption of homemade and ready-to-drink SSB was estimated from a single 24 h dietary recall, accounting for socio-demographic and health-related variables. Regression models were fitted to assess which variables were linked to a high/low SSB consumption. There were 913 people and mean age was 37.7 years (95% confidence interval (CI): 36.9–38.6). Mean consumption (8 oz servings/day) of homemade SSB (1.2) doubled that of ready-to-drink SSB (0.5). The intake of homemade and ready-to-drink SSB was higher in men (1.3 and 0.7) than women (1.1 and 0.3). The intake of ready-to-drink SSB was higher in urban (0.6) compared to rural (0.2) populations. People aware of having diabetes had a lower consumption of both ready-to-drink (0.9 vs. 0.4) and homemade SSB (1.3 vs. 0.8) than those unaware of having diabetes. Male sex and living in urban locations were associated with higher ready-to-drink SSB intake. Older age was associated with a higher intake of homemade SSB. Amongst Peruvian adults, the consumption of SSB products (particularly homemade) remains high. Population-wide interventions should also aim to improve awareness of the nutritional components of homemade beverages.

Objective To determine the agreement between the cardiovascular disease (CVD) risk predictions computed with the WHO non-laboratory-based model and laboratory-based model in a nationally representative sample of Peruvian adults. Design Cross-sectional analysis of a national health survey. Methods Absolute CVD risk was computed with the 2019 WHO laboratory-based and non-laboratory-based models. The risk predictions from both models were compared with Bland-Altman plots, Lin’s concordance coefficient correlation (LCCC), and kappa statistics, stratified by sex, age, body mass index categories, smoking and diabetes status. Results 663 people aged 30–59 years were included in the analysis. Overall, there were no substantial differences between the mean CVD risk computed with the laboratory-based model 2.0% (95% CI 1.8% to 2.2%) and the non-laboratory-based model 2.0% (95% CI 1.8% to 2.1%). In the Bland-Altman plots, the limits of agreement were the widest among people with diabetes (−0.21; 4.37) compared with people without diabetes (−1.17; 0.95). The lowest agreement as per the LCCC was also seen in people with diabetes (0.74 (95% CI 0.63 to 0.82)), the same was observed with the kappa statistic (kappa=0.36). In general, agreement between the scores was appropriate in terms of clinical significance. Conclusions The absolute cardiovascular predicted risk was similar between the laboratory-based and non-laboratory-based 2019 WHO cardiovascular risk models. Pending validation from longitudinal studies, the non-laboratory-based model (instead of the laboratory-based) could be used when assessing CVD risk in Peruvian population.

Background: National and subnational characterization of birthweight profiles lacks in low- and middleincome countries, yet these are needed for monitoring the progress of national and global nutritional targets. We aimed to describe birthweight indicators at the national and subnational levels in Peru (2012-2019), and by selected correlates. Methods: We studied mean birthweight (g), low birthweight (<2,500 g) and small for gestational age (according to international growth curves) prevalences. We analysed the national birth registry and summarized the three birthweight indicators at the national, regional, and province level, also by geographic area (Coast, Highlands, and Amazon). With individual-level data from the mother, we described the birthweight indicators by age, educational level and healthcare provider. Following an ecological approach (province level), we described the birthweight indicators by human development index (HDI), altitude above sea level, proportion of the population living in poverty and proportion of rural population. Findings: Mean birthweight was always the lowest in the Highlands (2,954 g in 2019) yet the highest in the Coast (3,516 g in 2019). The same was observed for low birthweight and small for gestational age. In regions with Coast and Highlands, the birthweight indicators worsen from the Coast to the Highlands; the largest absolute difference in mean birthweight between Coast and Highlands in the same region was 367 g. All birthweight indicators were the worst in mothers with none/initial education, while they improved with higher HDI. Interpretation: This analysis suggests that interventions are needed at the province level, given the large differences observed between Coast and Highlands even in the same region. (c) 2021TheAuthor(s). PublishedbyElsevierLtd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)